package com.micro.ai.models.service.impl;

import com.micro.ai.commons.exception.BusinessException;
import com.micro.ai.models.entity.FineTunedModel;
import com.micro.ai.models.service.ModelDeploymentService;
import lombok.extern.slf4j.Slf4j;
import org.springframework.stereotype.Service;

/**
 * HuggingFace模型部署服务实现
 * 
 * 功能说明：
 * 将微调后的模型上传到HuggingFace Hub，使其可以通过API调用
 * 
 * 实现步骤：
 * 1. 使用HuggingFace API上传模型文件
 * 2. 创建模型仓库
 * 3. 获取模型访问URL
 * 4. 验证模型可用性
 * 
 * @author micro-ai
 * @since 0.0.1
 */
@Slf4j
@Service
public class HuggingFaceDeploymentServiceImpl implements ModelDeploymentService {

    // @Value("${huggingface.api.token:}")
    // private String huggingFaceApiToken;

    @Override
    public ModelDeploymentService.DeploymentInfo deployModel(FineTunedModel model) {
        log.info("开始部署模型到HuggingFace: modelId={}, modelName={}", 
                model.getId(), model.getModelName());
        
        ModelDeploymentService.DeploymentInfo info = new ModelDeploymentService.DeploymentInfo();
        
        try {
            // 1. 构建模型仓库名称
            String repoName = "micro-ai/" + model.getModelName().toLowerCase().replaceAll("[^a-z0-9-]", "-");
            
            // 2. 使用HuggingFace API上传模型
            // 实际实现需要使用HuggingFace Java客户端或REST API
            /*
            HuggingFaceClient client = new HuggingFaceClient(huggingFaceApiToken);
            
            // 创建仓库（如果不存在）
            client.createRepo(repoName, "model");
            
            // 上传模型文件
            if (model.getModelPath() != null) {
                Path modelPath = Paths.get(model.getModelPath());
                client.uploadFile(repoName, modelPath);
            }
            
            // 上传配置文件
            uploadConfigFiles(repoName, model);
            
            // 获取模型URL
            String modelUrl = "https://huggingface.co/" + repoName;
            */
            
            // 当前为示例实现
            String modelUrl = "https://huggingface.co/" + repoName;
            
            info.setModelServiceId(repoName);
            info.setApiEndpoint(modelUrl);
            info.setStatus("deployed");
            
            log.info("模型部署成功: modelId={}, repoName={}", model.getId(), repoName);
            
        } catch (Exception e) {
            log.error("部署模型到HuggingFace失败: modelId={}, error={}", 
                    model.getId(), e.getMessage(), e);
            info.setStatus("failed");
            throw new BusinessException("M0003", "部署模型失败: " + e.getMessage());
        }
        
        return info;
    }

    @Override
    public boolean verifyDeployment(ModelDeploymentService.DeploymentInfo deploymentInfo) {
        log.info("验证模型部署: modelServiceId={}", deploymentInfo.getModelServiceId());
        
        try {
            // 方案1: 调用HuggingFace API检查模型是否存在
            /*
            HuggingFaceClient client = new HuggingFaceClient(huggingFaceApiToken);
            ModelInfo modelInfo = client.getModelInfo(deploymentInfo.getModelServiceId());
            return modelInfo != null;
            */
            
            // 方案2: 发送测试请求验证模型可用
            /*
            String testInput = "Hello, world!";
            String response = callModelAPI(deploymentInfo.getApiEndpoint(), testInput);
            return response != null && !response.isEmpty();
            */
            
            // 当前为示例实现
            log.warn("模型验证逻辑未实现，返回true");
            return true;
            
        } catch (Exception e) {
            log.error("验证模型部署失败: modelServiceId={}, error={}", 
                    deploymentInfo.getModelServiceId(), e.getMessage(), e);
            return false;
        }
    }

    @Override
    public void undeployModel(ModelDeploymentService.DeploymentInfo deploymentInfo) {
        log.info("取消模型部署: modelServiceId={}", deploymentInfo.getModelServiceId());
        
        try {
            // 使用HuggingFace API删除模型仓库
            /*
            HuggingFaceClient client = new HuggingFaceClient(huggingFaceApiToken);
            client.deleteRepo(deploymentInfo.getModelServiceId());
            */
            
            log.info("模型部署已取消: modelServiceId={}", deploymentInfo.getModelServiceId());
            
        } catch (Exception e) {
            log.error("取消模型部署失败: modelServiceId={}, error={}", 
                    deploymentInfo.getModelServiceId(), e.getMessage(), e);
            throw new BusinessException("M0003", "取消部署失败: " + e.getMessage());
        }
    }

    /**
     * 上传配置文件（如tokenizer配置、模型配置等）
     */
    private void uploadConfigFiles(String repoName, FineTunedModel model) {
        // 上传tokenizer配置、config.json等文件
        // 这些文件通常是训练框架生成的
    }
}

